Data Science · Data Bias
Virginia SOL DS.3
Virginia SOL DS.3 is part of the Data Bias strand in Data Science (Math). Under this Standards of Learning objective, students recognize data literacy and identify biases in existing analyses and visualizations. Below is what DS.3 covers in plain language, the specific skills it is assessed on, the key concepts to review, and how to practice DS.3 for the Virginia SOL test.
What SOL DS.3 means
Recognize data literacy and identify biases in existing analyses and visualizations.
Skills you’ll practice for DS.3
- Formulate questions to identify potential data biases in analyses or visualizations.
- Read and explain data summaries and visualizations in nontechnical terms.
- Identify potential data biases and discuss their effects on analysis and decision-making.
- Identify privacy and consumer protection issues in data presentation.
- Describe types of data collected by business, industry, and government entities and their uses.
Key concepts covered by DS.3
- bias identification
- data literacy
- bias questions
- data summarization
- visualization interpretation
- nontechnical communication
- data bias effects
- bias analysis
- decision-making impact
- data privacy
- consumer protection
- data presentation issues
- data collection types
- business data
- government data
- data usage
How to study and practice SOL DS.3
Start with a quick diagnostic to see whether DS.3 is already solid, then work each skill above with guided notes, flashcards, and SOL-style practice questions. For official released items, see our Virginia SOL practice tests guide and how to study for the SOL test.
Related Data Science standards in Data Bias
- DS.4 — Identify biases in data collection and understand implications and privacy issues.
Frequently asked questions about SOL DS.3
What is Virginia SOL DS.3?
SOL DS.3 is a Data Science Standard of Learning in the Data Bias strand. It expects students to recognize data literacy and identify biases in existing analyses and visualizations.
What skills does SOL DS.3 cover?
SOL DS.3 is assessed on 5 skills: formulate questions to identify potential data biases in analyses or visualizations; read and explain data summaries and visualizations in nontechnical terms; identify potential data biases and discuss their effects on analysis and decision-making; identify privacy and consumer protection issues in data presentation; describe types of data collected by business, industry, and government entities and their uses.
What strand of Data Science is SOL DS.3 in?
SOL DS.3 belongs to the Data Bias reporting strand of the Data Science Virginia Standards of Learning.
How do I study and practice for SOL DS.3?
Start with a diagnostic to see whether DS.3 is already solid, then work the 5 skills above with guided notes, flashcards, and SOL-style practice questions. For official released items, see the Virginia SOL practice tests guide.